Please use this identifier to cite or link to this item:
|Title:||View-based 3D model retrieval with probabilistic graph model|
Probabilistic graph model
|Source:||Gao, Y., Tang, J., Li, H., Dai, Q., Zhang, N. (2010). View-based 3D model retrieval with probabilistic graph model. Neurocomputing 73 (10-12) : 1900-1905. ScholarBank@NUS Repository. https://doi.org/10.1016/j.neucom.2009.11.050|
|Abstract:||In this paper, we present a view-based 3D model retrieval algorithm using probabilistic graph model. In this work, five circle camera arrays are employed, and five groups of views are captured from each 3D model. Each captured view set is modeled as a first order Markov Chain. The task of 3D model retrieval is defined as a probabilistic analysis procedure, and the comparison between the query and other 3D models is changed to compute the conditional probabilities of 3D models in the database given the query model. The purpose to search 3D model is to find the maximal a posterior probability of the models in the database given the query model. Then, we present a solution to estimate the conditional probabilities. The proposed 3D model retrieval algorithm has been evaluated on the NTU 3D model database. Experimental results and comparison with other methods show the effectiveness of the proposed approach. © 2010.|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Feb 15, 2018
WEB OF SCIENCETM
checked on Feb 7, 2018
checked on Feb 20, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.